IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v387y2008i24p6190-6200.html
   My bibliography  Save this article

Analyzing open-source software systems as complex networks

Author

Listed:
  • Zheng, Xiaolong
  • Zeng, Daniel
  • Li, Huiqian
  • Wang, Feiyue

Abstract

Software systems represent one of the most complex man-made artifacts. Understanding the structure of software systems can provide useful insights into software engineering efforts and can potentially help the development of complex system models applicable to other domains. In this paper, we analyze one of the most popular open-source Linux meta packages/distributions called the Gentoo Linux. In our analysis, we model software packages as nodes and dependencies among them as edges. Our empirical results show that the resulting Gentoo network cannot be easily explained by existing complex network models. This in turn motivates our research in developing two new network growth models in which a new node is connected to an old node with the probability that depends not only on the degree but also on the “age” of the old node. Through computational and empirical studies, we demonstrate that our models have better explanatory power than the existing ones. In an effort to further explore the properties of these new models, we also present some related analytical results.

Suggested Citation

  • Zheng, Xiaolong & Zeng, Daniel & Li, Huiqian & Wang, Feiyue, 2008. "Analyzing open-source software systems as complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(24), pages 6190-6200.
  • Handle: RePEc:eee:phsmap:v:387:y:2008:i:24:p:6190-6200
    DOI: 10.1016/j.physa.2008.06.050
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437108005852
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2008.06.050?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. S. Redner, 1998. "How popular is your paper? An empirical study of the citation distribution," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 4(2), pages 131-134, July.
    2. Réka Albert & Hawoong Jeong & Albert-László Barabási, 1999. "Diameter of the World-Wide Web," Nature, Nature, vol. 401(6749), pages 130-131, September.
    3. Ergün, G. & Rodgers, G.J., 2002. "Growing random networks with fitness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 303(1), pages 261-272.
    4. Barabási, Albert-László & Ravasz, Erzsébet & Vicsek, Tamás, 2001. "Deterministic scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 299(3), pages 559-564.
    5. Barabási, Albert-László & Albert, Réka & Jeong, Hawoong, 1999. "Mean-field theory for scale-free random networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 272(1), pages 173-187.
    6. von Krogh, Georg & Spaeth, Sebastian & Lakhani, Karim R., 2003. "Community, joining, and specialization in open source software innovation: a case study," Research Policy, Elsevier, vol. 32(7), pages 1217-1241, July.
    7. Jayanth R. Banavar & Amos Maritan & Andrea Rinaldo, 1999. "Size and form in efficient transportation networks," Nature, Nature, vol. 399(6732), pages 130-132, May.
    8. Liu, Jianguo & Dang, Yanzhong & Wang, Zhongtuo & Zhou, Tao, 2006. "Relationship between the in-degree and out-degree of WWW," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 371(2), pages 861-869.
    9. Colizza, Vittoria & Flammini, Alessandro & Maritan, Amos & Vespignani, Alessandro, 2005. "Characterization and modeling of protein–protein interaction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(1), pages 1-27.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Hui & Zhao, Hai & Cai, Wei & Xu, Jiu-Qiang & Ai, Jun, 2013. "A modular attachment mechanism for software network evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2025-2037.
    2. Xiao, Guanping & Zheng, Zheng & Wang, Haoqin, 2017. "Evolution of Linux operating system network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 249-258.
    3. James Ma & Daniel Zeng & Huimin Zhao, 2012. "Modeling the growth of complex software function dependency networks," Information Systems Frontiers, Springer, vol. 14(2), pages 301-315, April.
    4. Rashid, Mehvish & Clarke, Paul M. & O’Connor, Rory V., 2019. "A systematic examination of knowledge loss in open source software projects," International Journal of Information Management, Elsevier, vol. 46(C), pages 104-123.
    5. Wang, Haoqin & Chen, Zhen & Xiao, Guanping & Zheng, Zheng, 2016. "Network of networks in Linux operating system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 447(C), pages 520-526.
    6. Cornelius Fritz & Co-Pierre Georg & Angelo Mele & Michael Schweinberger, 2024. "Vulnerability Webs: Systemic Risk in Software Networks," Papers 2402.13375, arXiv.org, revised Nov 2024.
    7. Youzhong Wang & Daniel Zeng & Bin Zhu & Xiaolong Zheng & Feiyue Wang, 2014. "Patterns of news dissemination through online news media: A case study in China," Information Systems Frontiers, Springer, vol. 16(4), pages 557-570, September.
    8. Šubelj, Lovro & Bajec, Marko, 2011. "Community structure of complex software systems: Analysis and applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(16), pages 2968-2975.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Hui & Zhao, Hai & Cai, Wei & Xu, Jiu-Qiang & Ai, Jun, 2013. "A modular attachment mechanism for software network evolution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2025-2037.
    2. Zhang, Zhongzhi & Rong, Lili & Comellas, Francesc, 2006. "High-dimensional random Apollonian networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 364(C), pages 610-618.
    3. Claes Andersson & Koen Frenken & Alexander Hellervik, 2006. "A Complex Network Approach to Urban Growth," Environment and Planning A, , vol. 38(10), pages 1941-1964, October.
    4. Yao, Xin & Zhang, Chang-shui & Chen, Jin-wen & Li, Yan-da, 2005. "On the formation of degree and cluster-degree correlations in scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 353(C), pages 661-673.
    5. Pi, Xiaochen & Tang, Longkun & Chen, Xiangzhong, 2021. "A directed weighted scale-free network model with an adaptive evolution mechanism," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    6. Blagus, Neli & Šubelj, Lovro & Bajec, Marko, 2012. "Self-similar scaling of density in complex real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2794-2802.
    7. He, Xuan & Zhao, Hai & Cai, Wei & Liu, Zheng & Si, Shuai-Zong, 2014. "Earthquake networks based on space–time influence domain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 407(C), pages 175-184.
    8. Duan, Shuyu & Wen, Tao & Jiang, Wen, 2019. "A new information dimension of complex network based on Rényi entropy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 529-542.
    9. Dávid Csercsik & Sándor Imre, 2017. "Cooperation and coalitional stability in decentralized wireless networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 64(4), pages 571-584, April.
    10. Chung-Yuan Huang & Chuen-Tsai Sun & Hsun-Cheng Lin, 2005. "Influence of Local Information on Social Simulations in Small-World Network Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-8.
    11. Colizza, Vittoria & Flammini, Alessandro & Maritan, Amos & Vespignani, Alessandro, 2005. "Characterization and modeling of protein–protein interaction networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(1), pages 1-27.
    12. He, Xuan & Zhao, Hai & Cai, Wei & Li, Guang-Guang & Pei, Fan-Dong, 2015. "Analyzing the structure of earthquake network by k-core decomposition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 34-43.
    13. Razdan, Ashok, 2013. "Networks in extensive air showers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 982-986.
    14. Laurienti, Paul J. & Joyce, Karen E. & Telesford, Qawi K. & Burdette, Jonathan H. & Hayasaka, Satoru, 2011. "Universal fractal scaling of self-organized networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(20), pages 3608-3613.
    15. Chen, Qinghua & Shi, Dinghua, 2004. "The modeling of scale-free networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 335(1), pages 240-248.
    16. Arenas, Alex & Diaz-Guilera, Albert & Perez, Conrad J. & Vega-Redondo, Fernando, 2002. "Self-organized criticality in evolutionary systems with local interaction," Journal of Economic Dynamics and Control, Elsevier, vol. 26(12), pages 2115-2142, October.
    17. Yilmaz, Ergin, 2014. "Impacts of hybrid synapses on the noise-delayed decay in scale-free neural networks," Chaos, Solitons & Fractals, Elsevier, vol. 66(C), pages 1-8.
    18. Perc, Matjaž, 2007. "Effects of small-world connectivity on noise-induced temporal and spatial order in neural media," Chaos, Solitons & Fractals, Elsevier, vol. 31(2), pages 280-291.
    19. J. Esquivel-Gómez & R. E. Balderas-Navarro & P. D. Arjona-Villicaña & P. Castillo-Castillo & O. Rico-Trejo & J. Acosta-Elias, 2017. "On the Emergence of Islands in Complex Networks," Complexity, Hindawi, vol. 2017, pages 1-10, January.
    20. Pongou, Roland & Tchuente, Guy & Tondji, Jean-Baptiste, 2021. "Optimally Targeting Interventions in Networks during a Pandemic: Theory and Evidence from the Networks of Nursing Homes in the United States," GLO Discussion Paper Series 957, Global Labor Organization (GLO).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:387:y:2008:i:24:p:6190-6200. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.